评估柬埔寨洞里萨湖盆地北部的季节预报模式

IF 2.2 4区 地球科学 Q3 METEOROLOGY & ATMOSPHERIC SCIENCES
Libanda Brigadier, Ngeang Leak, Lim Hak, Khoeun Sokhom, Lonh Nrak, Ich Ilan, Chinn Rattana
{"title":"评估柬埔寨洞里萨湖盆地北部的季节预报模式","authors":"Libanda Brigadier,&nbsp;Ngeang Leak,&nbsp;Lim Hak,&nbsp;Khoeun Sokhom,&nbsp;Lonh Nrak,&nbsp;Ich Ilan,&nbsp;Chinn Rattana","doi":"10.1007/s13143-025-00393-9","DOIUrl":null,"url":null,"abstract":"<div><p>Accurate seasonal climate forecasts are vital for regions like Cambodia's Northern Tonle Sap Basin (NTSB), where agriculture is closely tied to rainfall patterns. While most studies have focused on the TSB, the northern areas, crucial contributors to Cambodia's national food basket, have remained largely unstudied. Here, this gap is addressed by evaluating the performance of 8 state-of-the-art seasonal forecast models from the Copernicus Climate Change Service (C3S) over a 24-year hindcast period (1993–2016). The evaluation is bolstered by ground-based data from 38 agrometeorological stations. Among the models, the Ensemble, the Japan Meteorological Agency (JMA) model, and the European Centre for Medium-Range Weather Forecasts (ECMWF) model emerged as top performers, with the Ensemble particularly excelling in replicating both temporal and spatial precipitation patterns, making it invaluable for agrometeorological applications. The Ensemble demonstrates particularly strong performance in regions such as western Oddar Meanchey and eastern Preah Vihear, where biases are less than 5%. To tailor the Ensemble to the specific climatic and geographic context of the NTSB, we refined it using the Delta Change technique, and this reduced biases even further to &lt; 1%. Our study not only contributes to improving the precision of agrometeorological advisories in a key, but under-researched region, but also sets a precedent for how regional climate forecasting can be enhanced through context-specific model evaluations and corrections. These findings provide a practical framework for supporting resilient agricultural strategies in areas vulnerable to climate change, bridging a critical gap between climate science and agricultural practice.</p></div>","PeriodicalId":8556,"journal":{"name":"Asia-Pacific Journal of Atmospheric Sciences","volume":"61 2","pages":""},"PeriodicalIF":2.2000,"publicationDate":"2025-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Evaluating Seasonal Forecast Models for Cambodia’s Northern Tonle Sap Basin\",\"authors\":\"Libanda Brigadier,&nbsp;Ngeang Leak,&nbsp;Lim Hak,&nbsp;Khoeun Sokhom,&nbsp;Lonh Nrak,&nbsp;Ich Ilan,&nbsp;Chinn Rattana\",\"doi\":\"10.1007/s13143-025-00393-9\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Accurate seasonal climate forecasts are vital for regions like Cambodia's Northern Tonle Sap Basin (NTSB), where agriculture is closely tied to rainfall patterns. While most studies have focused on the TSB, the northern areas, crucial contributors to Cambodia's national food basket, have remained largely unstudied. Here, this gap is addressed by evaluating the performance of 8 state-of-the-art seasonal forecast models from the Copernicus Climate Change Service (C3S) over a 24-year hindcast period (1993–2016). The evaluation is bolstered by ground-based data from 38 agrometeorological stations. Among the models, the Ensemble, the Japan Meteorological Agency (JMA) model, and the European Centre for Medium-Range Weather Forecasts (ECMWF) model emerged as top performers, with the Ensemble particularly excelling in replicating both temporal and spatial precipitation patterns, making it invaluable for agrometeorological applications. The Ensemble demonstrates particularly strong performance in regions such as western Oddar Meanchey and eastern Preah Vihear, where biases are less than 5%. To tailor the Ensemble to the specific climatic and geographic context of the NTSB, we refined it using the Delta Change technique, and this reduced biases even further to &lt; 1%. Our study not only contributes to improving the precision of agrometeorological advisories in a key, but under-researched region, but also sets a precedent for how regional climate forecasting can be enhanced through context-specific model evaluations and corrections. These findings provide a practical framework for supporting resilient agricultural strategies in areas vulnerable to climate change, bridging a critical gap between climate science and agricultural practice.</p></div>\",\"PeriodicalId\":8556,\"journal\":{\"name\":\"Asia-Pacific Journal of Atmospheric Sciences\",\"volume\":\"61 2\",\"pages\":\"\"},\"PeriodicalIF\":2.2000,\"publicationDate\":\"2025-03-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Asia-Pacific Journal of Atmospheric Sciences\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s13143-025-00393-9\",\"RegionNum\":4,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"METEOROLOGY & ATMOSPHERIC SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Asia-Pacific Journal of Atmospheric Sciences","FirstCategoryId":"89","ListUrlMain":"https://link.springer.com/article/10.1007/s13143-025-00393-9","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"METEOROLOGY & ATMOSPHERIC SCIENCES","Score":null,"Total":0}
引用次数: 0

摘要

准确的季节性气候预报对柬埔寨北部洞里萨湖盆地(NTSB)等农业与降雨模式密切相关的地区至关重要。虽然大多数研究都集中在TSB地区,但对柬埔寨国家粮食篮子的关键贡献者北部地区的研究基本上仍未得到研究。本文通过评估来自哥白尼气候变化服务(C3S)的8个最先进的季节预报模式在24年预测期(1993-2016)的表现来解决这一差距。该评估得到了38个农业气象站的地面数据的支持。在这些模型中,Ensemble模型、日本气象厅(JMA)模型和欧洲中期天气预报中心(ECMWF)模型表现最好,其中Ensemble模型在复制时空降水模式方面表现尤为出色,对农业气象应用具有不可估量的价值。Ensemble在Oddar Meanchey西部和Preah Vihear东部等地区的表现尤为突出,这些地区的偏差低于5%。为了根据NTSB的特定气候和地理环境来调整集合,我们使用Delta变化技术对其进行了改进,这将偏差进一步降低到1%。我们的研究不仅有助于提高一个关键但研究不足的地区的农业气象预报的精度,而且还为如何通过具体情况的模式评估和修正来加强区域气候预报开创了先例。这些发现为支持易受气候变化影响地区的抗灾农业战略提供了一个实用框架,弥合了气候科学与农业实践之间的重大差距。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Evaluating Seasonal Forecast Models for Cambodia’s Northern Tonle Sap Basin

Evaluating Seasonal Forecast Models for Cambodia’s Northern Tonle Sap Basin

Accurate seasonal climate forecasts are vital for regions like Cambodia's Northern Tonle Sap Basin (NTSB), where agriculture is closely tied to rainfall patterns. While most studies have focused on the TSB, the northern areas, crucial contributors to Cambodia's national food basket, have remained largely unstudied. Here, this gap is addressed by evaluating the performance of 8 state-of-the-art seasonal forecast models from the Copernicus Climate Change Service (C3S) over a 24-year hindcast period (1993–2016). The evaluation is bolstered by ground-based data from 38 agrometeorological stations. Among the models, the Ensemble, the Japan Meteorological Agency (JMA) model, and the European Centre for Medium-Range Weather Forecasts (ECMWF) model emerged as top performers, with the Ensemble particularly excelling in replicating both temporal and spatial precipitation patterns, making it invaluable for agrometeorological applications. The Ensemble demonstrates particularly strong performance in regions such as western Oddar Meanchey and eastern Preah Vihear, where biases are less than 5%. To tailor the Ensemble to the specific climatic and geographic context of the NTSB, we refined it using the Delta Change technique, and this reduced biases even further to < 1%. Our study not only contributes to improving the precision of agrometeorological advisories in a key, but under-researched region, but also sets a precedent for how regional climate forecasting can be enhanced through context-specific model evaluations and corrections. These findings provide a practical framework for supporting resilient agricultural strategies in areas vulnerable to climate change, bridging a critical gap between climate science and agricultural practice.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Asia-Pacific Journal of Atmospheric Sciences
Asia-Pacific Journal of Atmospheric Sciences 地学-气象与大气科学
CiteScore
5.50
自引率
4.30%
发文量
34
审稿时长
>12 weeks
期刊介绍: The Asia-Pacific Journal of Atmospheric Sciences (APJAS) is an international journal of the Korean Meteorological Society (KMS), published fully in English. It has started from 2008 by succeeding the KMS'' former journal, the Journal of the Korean Meteorological Society (JKMS), which published a total of 47 volumes as of 2011, in its time-honored tradition since 1965. Since 2008, the APJAS is included in the journal list of Thomson Reuters’ SCIE (Science Citation Index Expanded) and also in SCOPUS, the Elsevier Bibliographic Database, indicating the increased awareness and quality of the journal.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信